Dementia detection from speech using machine learning and deep learning architectures

MR Kumar, S Vekkot, S Lalitha, D Gupta, VJ Govindraj… - Sensors, 2022 - mdpi.com
Dementia affects the patient's memory and leads to language impairment. Research has
demonstrated that speech and language deterioration is often a clear indication of dementia …

F-test feature selection in Stacking ensemble model for breast cancer prediction

R Dhanya, IR Paul, SS Akula, M Sivakumar… - Procedia Computer …, 2020 - Elsevier
Cancer data sets contains many details of patient information, out of which only a few
attributes contribute in predicting the accurate stage of cancer. Certain attributes of the entire …

A comparative study for breast cancer prediction using machine learning and feature selection

R Dhanya, IR Paul, SS Akula… - … and control systems …, 2019 - ieeexplore.ieee.org
While there are many factors which could contribute to the occurrence of breast cancer, it is
very difficult to attribute the exact environmental and other factors contributing to it, but still it …

Deep learning-based approach for multi-stage diagnosis of Alzheimer's disease

V Ravi, G EA, S KP - Multimedia Tools and Applications, 2024 - Springer
Alzheimer's Disease (AD) is a common neurological brain disorder that causes the brain
cells to die and shrink (Atrophy) gradually, resulting in a continuous decline in one's ability to …

Alzheimer's disease detection using convolutional neural networks and transfer learning based methods

M Zaabi, N Smaoui, H Derbel… - 2020 17th International …, 2020 - ieeexplore.ieee.org
Alzheimer's disease (AD) remains a major public health problem. This neurodegenerative
pathology affects generally old people. Its symptoms are loss of memory followed over the …

Analysis of machine learning and deep learning algorithms for detection of brain disorders using MRI data

D Sudharsan, S Isha Indhu, KS Kumar… - Artificial Intelligence on …, 2022 - Springer
Brain diseases impact more than 1 billion people worldwide and include a wide spectrum of
diseases and disorders such as stroke, Alzheimer's, Parkinson's, Epilepsy and other Seizure …

Diabetic Retinopathy Detection using Deep Learning Methodology

AV Kumar, AS Babu - 2022 IEEE 3rd Global Conference for …, 2022 - ieeexplore.ieee.org
Diabetic retinopathy is a human retinal sickness that makes harm the veins in the retina.
Individuals with diabetics have high glucose level that harm the veins. These blood vessels …

Alzheimers Disease Detection Using MIC and MLP

S Reeha, HM Basavadeepthi… - 2023 14th International …, 2023 - ieeexplore.ieee.org
Dementia, a brain-related illness, is afflicting numerous individuals worldwide, and it is
imperative to detect the disease at its early stages. Alzheimer's disease (AD), which affects …

Early classification of abnormal health using longitudinal structural mri data

K Devika, VRM Oruganti - 2020 IEEE 17th India Council …, 2020 - ieeexplore.ieee.org
This paper investigates extensively Machine Learning (ML) algorithms for abnormal health
conditions using two sessions of Structural Magnetic Resonance Imaging (sMRI) data. First …

Exploring Adversarial Attacks and Countermeasures in Image Classification and Object Detection: A Survey

A JL, P CP - Available at SSRN 4607819, 2023 - papers.ssrn.com
Deep learning plays a crucial part in Artificial Intelligence applications like Object Detection,
Cyber Security, Natural Language Processing, Robotics, Bioinformatics, Medical Imaging …